Compute engine makers can do all they want to bring the performance of their devices on par or even reasonably close to that of Nvidia’s various GPU accelerators, but until they have something akin to the NVLink and NVSwitch memory fabric that Nvidia uses to leverage the performance of many GPUs at bandwidths that dwarf PCI-Express switches and latencies that dwarf Ethernet interconnects, they can never catch up. …
It is safe to say in 2025 that the best job in the world is the chief executive officer of Nvidia, and that the company’s co-founder, Jensen Huang, has steered the company to great heights as much as fellow co-founders Thomas Watson ever did with International Business Machines, Larry Ellison ever did with Oracle, and Steve Jobs ever did with Apple Computer. …
It has become a well known fact these days that the switches that are used to interconnect distributed systems are not the most expensive part of that network, but rather it is the optical transceivers and fiber optic cables that comprise the bulk of the cost. …
When you are designing applications that run across the scale of an entire datacenter and that are comprised of hundreds to thousands of microservices running on countless individual servers and that have to be called within a matter of microseconds to give the illusion of a monolithic application, building fully connected, high bi-section bandwidth Clos networks is a must. …
The generative AI revolution is making strange bedfellows, as revolutions and emerging monopolies that capitalize on them often do. …
For the past five years, since Nvidia acquired InfiniBand and Ethernet switch and network interface card supplier Mellanox, people have been wondering what the split is between compute and networking in the Nvidia datacenter business that has exploded in growth and now represents most of revenue for each quarter. …
While a lot of people focus on the floating point and integer processing architectures of various kinds of compute engines, we are spending more and more of our time looking at memory hierarchies and interconnect hierarchies. …
We like datacenter compute engines here at The Next Platform, but as the name implies, what we really like are platforms – how compute, storage, networking, and systems software are brought together to create a platform on which to build applications. …
Not everybody can afford an Nvidia DGX AI server loaded up with the latest “Hopper” H100 GPU accelerators or even one of its many clones available from the OEMs and ODMs of the world. …
You can’t be certain about a lot of things in the world these days, but one thing you can count on is the voracious appetite for parallel compute, high bandwidth memory, and high bandwidth networking for AI training workloads. …
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